🧠 Medical AI Dashboard

📌 Overview

This project is a multi-modal AI system that combines deep learning and machine learning to assist in medical diagnosis.

It performs:

• 🧠 Brain tumor detection from MRI images (CNN)
• ❤️ Heart disease prediction using patient data (ML)
• 🔥 Explainable AI using Grad-CAM

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🚀 Features

• Upload MRI scan and get tumor classification
• Enter patient details for heart disease prediction
• Grad-CAM visualization to highlight important regions
• Interactive web app using Streamlit
• Clean and user-friendly UI

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🛠️ Tech Stack

• Python
• PyTorch
• Scikit-learn
• Streamlit
• OpenCV
• Matplotlib / Seaborn

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📊 Model Details

🧠 MRI Model (CNN)

• Input: MRI image

• Output: Tumor type (glioma, meningioma, no tumor, pituitary)

• Improvements:

  • Data augmentation
  • Dropout layer

• Accuracy: ~86%

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❤️ Tabular Model (Random Forest)

• Input: Patient health data
• Output: Heart disease risk
• Accuracy: ~98%

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🔍 Explainable AI

This project uses Grad-CAM to visualize which regions of MRI images influence model predictions, improving interpretability.

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📷 Demo

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▶️ How to Run

pip install -r requirements.txt
streamlit run app/app.py

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📁 Project Structure

Medical_AI_System/
├── app/
│   └── app.py
├── models/
├── notebooks/
├── requirements.txt
└── README.md

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💡 Future Improvements

• Deploy as a web service
• Use advanced models like ResNet
• Integrate unified medical dataset

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👨‍💻 Author

Jeffrin Merino J